## We have 132 observations with 102 columns.
We have 3 subjects (SIDs: CQ 1328, CQ 1424, CQ 1518) with duplicated observations.
In section, we check if the clocks are stable by comparing them in the duplicated observations.
Evaluate correlation/concordance between the duplicate pairs
Clocks / Age Accelerations
## Horvath EAA Hannum EAA PhenoAge EAA Skin&Blood EAA GrimAge EAA DNAmTL
## [1,] 0.05638483 2.678389 3.898440 0.6858806 0.7138976 0.04309056
## [2,] 2.80993321 1.122348 2.464987 0.8001586 1.6632470 0.04052281
## [3,] 1.23251949 0.732867 7.594791 2.9191094 1.0295776 0.02069328
## IEAA EEAA
## [1,] 0.3889968 3.667739
## [2,] 3.3026780 1.740232
## [3,] 0.9771748 3.076599
##
## Summary: :
## Horvath EAA Hannum EAA PhenoAge EAA Skin&Blood EAA GrimAge EAA DNAmTL
## mean 1.366279 1.511201 4.652739 1.468383 1.1355741 0.03476888
## sd 1.381639 1.029403 2.646780 1.257665 0.4834692 0.01225725
## IEAA EEAA
## mean 1.556283 2.8281897
## sd 1.540750 0.9874722
##
## Horvath EAA :
## type ICC F df1 df2 p
## Single_raters_absolute ICC1 0.9802908 100.4755 2 3 0.001783993
## Single_random_raters ICC2 0.9803666 165.2373 2 2 0.006015498
## Single_fixed_raters ICC3 0.9879690 165.2373 2 2 0.006015498
## Average_raters_absolute ICC1k 0.9900473 100.4755 2 3 0.001783993
## Average_random_raters ICC2k 0.9900860 165.2373 2 2 0.006015498
## Average_fixed_raters ICC3k 0.9939481 165.2373 2 2 0.006015498
##
## Hannum EAA :
## type ICC F df1 df2 p
## Single_raters_absolute ICC1 0.9241935 25.38296 2 3 0.01318018
## Single_random_raters ICC2 0.9242641 26.02300 2 2 0.03700552
## Single_fixed_raters ICC3 0.9259890 26.02300 2 2 0.03700552
## Average_raters_absolute ICC1k 0.9606035 25.38296 2 3 0.01318018
## Average_random_raters ICC2k 0.9606416 26.02300 2 2 0.03700552
## Average_fixed_raters ICC3k 0.9615725 26.02300 2 2 0.03700552
##
## PhenoAge EAA :
## type ICC F df1 df2 p
## Single_raters_absolute ICC1 0.3206087 1.943812 2 3 0.2874602
## Single_random_raters ICC2 0.3206087 1.943812 2 2 0.3396956
## Single_fixed_raters ICC3 0.3206087 1.943812 2 2 0.3396956
## Average_raters_absolute ICC1k 0.4855469 1.943812 2 3 0.2874602
## Average_random_raters ICC2k 0.4855469 1.943812 2 2 0.3396956
## Average_fixed_raters ICC3k 0.4855469 1.943812 2 2 0.3396956
##
## Skin&Blood EAA :
## type ICC F df1 df2 p
## Single_raters_absolute ICC1 0.3135357 1.91348 2 3 0.2913003
## Single_random_raters ICC2 0.3135357 1.91348 2 2 0.3432322
## Single_fixed_raters ICC3 0.3135357 1.91348 2 2 0.3432322
## Average_raters_absolute ICC1k 0.4773919 1.91348 2 3 0.2913003
## Average_random_raters ICC2k 0.4773919 1.91348 2 2 0.3432322
## Average_fixed_raters ICC3k 0.4773919 1.91348 2 2 0.3432322
##
## GrimAge EAA :
## type ICC F df1 df2 p
## Single_raters_absolute ICC1 0.9807695 103.0017 2 3 0.001719697
## Single_random_raters ICC2 0.9809233 636.9022 2 2 0.001567638
## Single_fixed_raters ICC3 0.9968647 636.9022 2 2 0.001567638
## Average_raters_absolute ICC1k 0.9902914 103.0017 2 3 0.001719697
## Average_random_raters ICC2k 0.9903698 636.9022 2 2 0.001567638
## Average_fixed_raters ICC3k 0.9984299 636.9022 2 2 0.001567638
##
## DNAmTL :
## type ICC F df1 df2 p
## Single_raters_absolute ICC1 0.9898538 196.1186 2 3 0.000661295
## Single_random_raters ICC2 0.9898538 196.1186 2 2 0.005073088
## Single_fixed_raters ICC3 0.9898538 196.1186 2 2 0.005073088
## Average_raters_absolute ICC1k 0.9949010 196.1186 2 3 0.000661295
## Average_random_raters ICC2k 0.9949010 196.1186 2 2 0.005073088
## Average_fixed_raters ICC3k 0.9949010 196.1186 2 2 0.005073088
##
## IEAA :
## type ICC F df1 df2 p
## Single_raters_absolute ICC1 0.9750351 79.11262 2 3 0.002538238
## Single_random_raters ICC2 0.9750756 90.94104 2 2 0.010876536
## Single_fixed_raters ICC3 0.9782469 90.94104 2 2 0.010876536
## Average_raters_absolute ICC1k 0.9873598 79.11262 2 3 0.002538238
## Average_random_raters ICC2k 0.9873805 90.94104 2 2 0.010876536
## Average_fixed_raters ICC3k 0.9890039 90.94104 2 2 0.010876536
##
## EEAA :
## type ICC F df1 df2 p
## Single_raters_absolute ICC1 0.8698274 14.36421 2 3 0.02907429
## Single_random_raters ICC2 0.8698274 14.36421 2 2 0.06508632
## Single_fixed_raters ICC3 0.8698274 14.36421 2 2 0.06508632
## Average_raters_absolute ICC1k 0.9303825 14.36421 2 3 0.02907429
## Average_random_raters ICC2k 0.9303825 14.36421 2 2 0.06508632
## Average_fixed_raters ICC3k 0.9303825 14.36421 2 2 0.06508632
Number of observations removed: 3
Number of missing values in baseline covariates:
## Age BMI predictedGender fueltype stovetype
## 0 0 0 0 0
Number of missing values in ambient exposure measurements covariates:
## bap_air pm25_air ANY_air BPE_air BaA_air BbF_air BkF_air CHR_air
## 5 0 41 5 5 5 5 5
## DBA_air FLT_air FLU_air IPY_air NAP_air PHE_air PYR_air
## 5 5 41 5 41 41 5
Number of missing values in urinary measurements covariates:
## Benzanthracene_Chrysene_urine Naphthalene_urine
## 2 0
## Methylnaphthalene_2_urine Methylnaphthalene_1_urine
## 9 4
## Acenaphthene_urine Phenanthrene_Anthracene_urine
## 0 0
## Fluoranthene_urine Pyrene_urine
## 0 18
Observations with different number of total missing measurements:
##
## Number of missing measurements: 0 1 2 3 4 5 6 14 15
## Number of observations: 73 10 4 1 27 8 1 3 2
Observations with different number of missing air exposure measurements:
##
## Number of missing measurements: 0 4 14
## Number of observations: 88 36 5
Observations with different number of missing urinary measurements:
##
## Number of missing measurements: 0 1 2 3
## Number of observations: 103 20 5 1
Number of observations removed: 0
| Characteristic | N = 1291 |
|---|---|
| Age | 58 (15) |
| BMI | 22.0 (3.5) |
| predictedGender | |
| female | 129 / 129 (100%) |
| fueltype | |
| Plant | 4 / 129 (3.1%) |
| Smokeles | 18 / 129 (14%) |
| Smoky | 98 / 129 (76%) |
| Wood | 9 / 129 (7.0%) |
| stovetype | |
| FP | 11 / 129 (8.5%) |
| HS | 31 / 129 (24%) |
| LS | 30 / 129 (23%) |
| Mix | 37 / 129 (29%) |
| PS | 20 / 129 (16%) |
| DNAmAge | 59 (13) |
| DNAmAgeHannum | 60 (14) |
| DNAmPhenoAge | 56 (14) |
| DNAmAgeSkinBloodClock | 57 (13) |
| DNAmGrimAge | 56 (11) |
| DNAmTL | 6.82 (0.32) |
| AgeAccelerationResidual | -0.1 (4.4) |
| AgeAccelerationResidualHannum | -0.1 (4.0) |
| AgeAccelPheno | 0.0 (4.3) |
| DNAmAgeSkinBloodClockAdjAge | 0.0 (3.4) |
| AgeAccelGrim | -0.09 (2.99) |
| DNAmTLAdjAge | 0.00 (0.18) |
| IEAA | 0.0 (4.1) |
| EEAA | -0.1 (5.1) |
| bap_air | 65 (87) |
| (Missing) | 5 |
| pm25_air | 197 (176) |
| ANY_air | 1,038 (1,792) |
| (Missing) | 41 |
| BPE_air | 71 (92) |
| (Missing) | 5 |
| BaA_air | 88 (145) |
| (Missing) | 5 |
| BbF_air | 106 (143) |
| (Missing) | 5 |
| BkF_air | 23 (32) |
| (Missing) | 5 |
| CHR_air | 83 (133) |
| (Missing) | 5 |
| DBA_air | 24 (36) |
| (Missing) | 5 |
| FLT_air | 60 (136) |
| (Missing) | 5 |
| FLU_air | 486 (680) |
| (Missing) | 41 |
| IPY_air | 43 (51) |
| (Missing) | 5 |
| NAP_air | 5,731 (8,737) |
| (Missing) | 41 |
| PHE_air | 730 (1,054) |
| (Missing) | 41 |
| PYR_air | 66 (139) |
| (Missing) | 5 |
| Benzanthracene_Chrysene_urine | 0.92 (3.17) |
| (Missing) | 2 |
| Naphthalene_urine | 224 (686) |
| Methylnaphthalene_2_urine | 46 (59) |
| (Missing) | 9 |
| Methylnaphthalene_1_urine | 20 (24) |
| (Missing) | 4 |
| Acenaphthene_urine | 7 (11) |
| Phenanthrene_Anthracene_urine | 204 (275) |
| Fluoranthene_urine | 21 (23) |
| Pyrene_urine | 0.71 (0.57) |
| (Missing) | 18 |
|
1
Mean (SD); n / N (%)
|
|
## DNAmAge DNAmAgeHannum DNAmPhenoAge
## 3.391653 3.380488 3.005900
## DNAmAgeSkinBloodClock DNAmGrimAge
## 2.585191 4.063720
| Characteristic | N = 2241 |
|---|---|
| brthFuel | |
| Mix | 101 / 220 (46%) |
| Smokeles | 9 / 220 (4.1%) |
| Smoky | 78 / 220 (35%) |
| Wood | 32 / 220 (15%) |
| (Missing) | 4 |
|
1
n / N (%)
|
|
| Characteristic | N = 1291 |
|---|---|
| brthFuel | |
| Mix | 54 / 126 (43%) |
| Smokeles | 7 / 126 (5.6%) |
| Smoky | 52 / 126 (41%) |
| Wood | 13 / 126 (10%) |
| (Missing) | 3 |
|
1
n / N (%)
|
|
| Characteristic | N = 2241 |
|---|---|
| cumFuel | |
| Mix | 168 / 224 (75%) |
| Smoky | 56 / 224 (25%) |
|
1
n / N (%)
|
|
| Characteristic | N = 1291 |
|---|---|
| cumFuel | |
| Mix | 87 / 129 (67%) |
| Smoky | 42 / 129 (33%) |
|
1
n / N (%)
|
|
| Characteristic | N = 2241 |
|---|---|
| fueltype | |
| Plant | 4 / 129 (3.1%) |
| Smokeles | 18 / 129 (14%) |
| Smoky | 98 / 129 (76%) |
| Wood | 9 / 129 (7.0%) |
| (Missing) | 95 |
|
1
n / N (%)
|
|
| Characteristic | N = 2241 |
|---|---|
| fueltype | |
| Plant | 4 / 129 (3.1%) |
| Smokeles | 18 / 129 (14%) |
| Smoky | 98 / 129 (76%) |
| Wood | 9 / 129 (7.0%) |
| (Missing) | 95 |
|
1
n / N (%)
|
|
## # A tibble: 6 × 14
## ids_LCW VISIT education_cat SbjctD_LEX loc_N loc_E grp dist_min
## <chr> <lgl> <dbl> <lgl> <dbl> <dbl> <chr> <dbl>
## 1 1824 NA 3 NA 26.2 104. LCW Clean Ctrl 0.347
## 2 1912 NA 5 NA 26.2 104. LCW Clean Ctrl 0.347
## 3 2276 NA 6 NA 26.2 104. LCW Clean Ctrl 0.347
## 4 4386 NA 2 NA 25.7 104. LCW Clean Ctrl 0.570
## 5 2394 NA 2 NA 26.2 104. LCW Clean Ctrl 0.607
## 6 2274 NA 5 NA 26.2 104. LCW Clean Ctrl 0.609
## # … with 6 more variables: inpatient_sms <dbl>, diagnosis_code_sms <dbl>,
## # enroll_age_sms <dbl>, diagnosis_eng_sms <chr>, econ_any_items <dbl>,
## # curr_commune <chr>